Cohort Study of Pioglitazone and Cancer Incidence in Patients With Diabetes
Bibliographic record
Abstract
OBJECTIVE: To explore whether treatment with pioglitazone was associated with risk of incident cancer at the 10 most common sites (prostate, female breast, lung/bronchus, endometrial, colon, non-Hodgkin lymphoma [NHL], pancreas, kidney/renal pelvis, rectal, and melanoma). RESEARCH DESIGN AND METHODS: A cohort study of 252,467 patients aged ≥40 years from the Kaiser Permanente Northern California Diabetes Registry was conducted. All prescriptions for diabetes medications were identified by pharmacy records. Cox proportional hazards models were used to examine the association between risk of incident cancer and ever use, duration, dose, and time since initiation of pioglitazone (modeled as time-dependent variables). RESULTS: In models adjusted for age, sex, year of cohort entry, race/ethnicity, income, smoking, glycemic control, diabetes duration, creatinine levels, congestive heart failure, and use of other diabetes medications, the hazard ratio (HR) for each cancer associated with ever use of pioglitazone ranged from 0.7 to 1.3, with all 95% CIs including 1.0. There was a suggestion of an increased risk of melanoma (HR 1.3 [95% CI 0.9-2.0]) and NHL (1.3 [1.0-1.8]) and a decreased risk of kidney/renal pelvis cancers (0.7 [0.4-1.1]) associated with ever use of pioglitazone. These associations were unaltered with increasing dose, duration, or time since first use. CONCLUSIONS: We found no clear evidence of an association between use of pioglitazone and risk of the incident cancers examined. Because the maximum duration of follow-up was fewer than 6 years after the initiation of pioglitazone, longer-term studies are needed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".